Artificial neural networks (ANNs) may be used by computing systems to learn tasks, such as identifying whether a particular object is present within an image. Neural networks include a collection of interconnected nodes that receive an input signal from an upstream node or source, process that input signal by applying a function to obtain a result, and provide the result to a downstream node or process. Neural networks may be trained by providing training data to the network to generate a result that can be compared to a desired result. In the case of supervised training, the training data may be pre-labeled with the desired result that serves as a supervisory signal. Functions applied at the nodes may be parametrized according to learnable parameters, and the result generated by the network can be adjusted closer to the desired result by adjusting the learnable parameters based on the supervisory signal.